Agile Isn’t Enough For Sustainable Business Growth: How Brands Can Use Marketing Experimentation To Spur Continual Innovation

Published: February 20, 2024

1marioThe internet, already a place where trends, products and platforms come and go with incredible speed and velocity, is changing faster than ever before.

Propelled by the rapid rise of artificial intelligence (AI), mass adoption by global communities (5.3 billion people are now online around the world) and consumers’ seeming insatiable demand for digital products and services, the internet and its vast web of interconnected ecosystems is changing before our eyes.

Understandably, businesses are trying to transform alongside it. Many are struggling to keep up.

With the digital landscape changing daily, staying ahead of the latest trends and consumer sentiment demands more than adapting to change. It requires brands and global enterprises to actively drive it.

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The Role Of Experimentation In Digital Marketing

Experimentation-as-a-service (EaaS) provides a framework for actively driving trends.

EaaS, a systematic approach to assessing the efficacy of marketing tools and techniques, isn’t a new concept. It is newly relevant, as AI and machine learning (ML) algorithms are making it more efficient, effective and impactful.

{loadposition GIAA}Most importantly, it allows brands to proactively shape their marketing strategies rather than perpetually reacting to market dynamics.

For maximum effectiveness, brands should test several aspects of their marketing campaigns, including content, design, user experience and channel strategies. In doing so, brands begin to understand consumer behaviors and preferences, elevating sustainability and business growth potential.

For instance, a social media campaign that is continuously monitored and tweaked based on user engagement metrics can achieve significantly higher reach and impact compared to a static campaign.

With EaaS, digital marketers and the brands they support can leverage often-enormous data sets to make their companies more customer-centric than ever before.

AI Data Analytics For Better Decision-Making

Data is an abundant resource for many brands and leveraging it to make informed decisions is often easier said than done.

For instance, global data volume is quickly approaching 175 zettabytes, an unfathomably large number that is the functional equivalent of creating a stack of Blu-ray discs that can reach the moon 23 times.

This deluge of digital information has made data-driven decision-making more of a talking point and less of an operational reality.

Today, less than a quarter of executives say they’ve successfully created data-driven organizations. Despite having more data than ever before, companies are less effective at using this information than they were four years ago.

AI and ML are helping to solve this problem. These technologies are excellent at data analysis, identifying patterns and producing actionable outcomes that would otherwise be unavailable to brands.

As the “Harvard Business Review” succinctly explains, “This means that as a firm gathers more customer data, it can feed that data into machine learning algorithms to improve its product or service, thereby attracting more customers, generating even more customer data.”

While products and services with weak data footprints will inherently provide less data, practically every brand can leverage this technology to create more insights that drive better decision-making processes.

The goal is to maximize personalization. Adobe reported that 71% of consumers say they expect companies to deliver personalized interactions, and with more than three-quarters getting frustrated with brands when they fail to deliver, this is a critical dynamic for effective digital marketing experimentation.

With the average person encountering more than 1,700 online advertisements every month, these personalized encounters are critical to cutting through the noise and maximize marketing ROI.

Make Marketing Experimentation A Priority In 2024

Learning to create a dynamic feedback loop between brands and consumers won’t happen overnight. However, making it a strategic priority in 2024 can significantly impact marketing strategy and ROI, enabling businesses to make informed, real-time decisions that fuel sustainable growth and market impact.

Put differently, using AI and machine learning to distill actionable insights from vast data sets enables brands to forge a dynamic feedback loop with their customers, leading to more effective decision-making and a robust competitive edge.

That’s the power of making change, not just responding to it.

Mario Peshev is the CEO of DevriX, a global WordPress agency providing scalable, long-term technical partnerships along with marketing and business consulting. He is also a Core contributor to the WordPress project, an Inbound Certified marketer and a multi-disciplined business owner with a wide scope of skills.

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